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Full Time Machine Learning Finance Jobs (NOW HIRING)

Eccalon LLC

Machine Learning Engineer

Detroit, MI

Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the Research and Development Team, where ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

Hang draws from years of deep expertise in loyalty, game design, and finance with employees from ... This person will implement and develop machine learning models to enhance our platform ...

Q2

Machine Learning Engineer

Austin, TX · On-site

Our mission is simple: build strong and diverse communities through innovative financial technology ... SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

Our mission is simple: build strong and diverse communities through innovative financial technology ... SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ...

ManTech International

Machine Learning Engineer

$128K - $214K/yr

... Type Full time Description & Requirements Elevate your career with MANTECH International ... The Machine Learning Engineer will leverage their strong technical background and knowledge to ...

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Full Time Machine Learning Finance information

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$25K

$92.6K

$135.5K

How much do full time machine learning finance jobs pay per year?

As of Jul 8, 2026, the average yearly pay for full time machine learning finance in the United States is $92,631.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $109,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Full Time Machine Learning Finance professional, and why are they important?

To thrive as a Full Time Machine Learning Finance professional, you need a solid background in quantitative analysis, statistics, computer science, and finance, usually supported by a relevant degree. Proficiency with programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with financial data systems are essential. Strong problem-solving abilities, attention to detail, and effective communication skills help you stand out in this field. These skills ensure the successful development and deployment of data-driven financial models that support better decision-making and risk management.

What is a Full Time Machine Learning Finance job?

A Full Time Machine Learning Finance job involves applying machine learning techniques and algorithms to financial data and problems. Professionals in this role develop predictive models for tasks such as risk assessment, trading strategies, fraud detection, and portfolio optimization. They work closely with financial analysts and data scientists to create solutions that can automate processes, improve decision-making, and identify patterns in large datasets. The role typically requires strong knowledge of both finance and advanced machine learning methods, as well as programming and data analysis skills.

What is the difference between Full Time Machine Learning Finance vs Full Time Data Scientist?

AspectFull Time Machine Learning FinanceFull Time Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of finance and machine learning certificationsDegree in Statistics, Computer Science, or related fields; data analysis and programming skills
Work EnvironmentFinancial institutions, hedge funds, banks, fintech companiesTech companies, consulting firms, finance, healthcare, retail
Industry UsageFinance-specific applications like risk modeling, algorithmic tradingBroad industry applications including marketing, healthcare, finance

Full Time Machine Learning Finance roles focus on applying machine learning techniques specifically to financial data and problems within financial institutions. In contrast, Full Time Data Scientist positions have a broader scope across various industries, utilizing data analysis and modeling skills to solve diverse business challenges. While both roles require strong technical skills, the finance-specific role emphasizes financial knowledge and applications.

What are some common challenges faced by machine learning professionals working in the finance sector?

Machine learning professionals in finance often encounter challenges such as dealing with sensitive and highly regulated data, ensuring model transparency and explainability for compliance purposes, and adapting to rapidly changing market conditions. Additionally, integrating machine learning models with existing financial systems and collaborating closely with domain experts, such as quantitative analysts and risk managers, are key parts of the role. Staying updated on both technological advancements and regulatory changes is also essential for success in this dynamic environment.
More about Full Time Machine Learning Finance jobs
What cities are hiring for Full Time Machine Learning Finance jobs? Cities with the most Full Time Machine Learning Finance job openings:
What are the most commonly searched types of Machine Learning Finance jobs? The most popular types of Machine Learning Finance jobs are:
What states have the most Full Time Machine Learning Finance jobs? States with the most job openings for Full Time Machine Learning Finance jobs include:
What job categories do people searching Full Time Machine Learning Finance jobs look for? The top searched job categories for Full Time Machine Learning Finance jobs are:
Full Time Machine Learning Finance jobs near you
Infographic showing various Full Time Machine Learning Finance job openings in the United States as of July 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $92,631 per year, or $44.5 per hour.

Machine Learning Engineer

Waypoint Human Capital

Huntsville, AL • On-site

Full-time

Re-posted 8 days ago

Job description

Position Title: Machine Learning Engineer
Position Type: Full-time, On-Site
Location: Huntsville, AL
Clearance: Active TS
Description:
Waypoint's client is seeking a Machine Learning Engineer to support mission-critical efforts within a secure environment at the Missile and Space Intelligence Center. This role focuses on developing, integrating, and operationalizing machine learning solutions that support advanced analytics and intelligence capabilities.
The selected candidate will work across the full machine learning lifecycle, from building data pipelines and training models to deploying and monitoring production systems. This position requires a strong blend of software engineering and data science expertise, with a focus on scalability, performance, and system integration.
Responsibilities:
•Integrate machine learning systems into existing software architectures and enterprise platforms
•Design, build, and optimize data pipelines to support model training and inference
•Develop, test, and deploy machine learning models into production environments
•Manage transition from prototype to production, including deployment pipelines and monitoring solutions
•Monitor model performance, including handling model drift, rollback, and failure scenarios
•Conduct experiments and testing to evaluate and improve model accuracy and performance
•Write clean, maintainable, and testable code in Python and related technologies
•Collaborate with cross-functional teams to integrate ML capabilities into mission systems
•Utilize CI/CD pipelines and GitOps practices to support automated deployment and version control
•Support development in Linux and Windows environments
Required:
•Active TS clearance (with ability to obtain TS/SCI with CI Polygraph)
•Bachelor's degree in Computer Science, Mathematics, Statistics, Physics, or related technical field
•Minimum 12+ years of overall experience, including 1-3 years working with machine learning frameworks
•Strong programming skills in Python
•Experience with machine learning frameworks, libraries, and data modeling techniques
•Solid understanding of the machine learning lifecycle
•Experience working with SQL and NoSQL databases
•Experience working in Linux and Windows environments
•Familiarity with CI/CD pipelines and Agile development methodologies
•Understanding of software design and system integration principles
Desired:
•Active TS/SCI with CI Polygraph (desired)
•Experience working with large-scale (petabyte-level) datasets
•Experience supporting multi-INT analytics environments
•Experience deploying, monitoring, and scaling machine learning models in production
•Experience with tools such as Docker, Jupyter Notebooks, PostgreSQL, GitLab, and GitHub
•Experience implementing GitOps workflows
•Experience working in secure or classified environment

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